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\section{Discussion}
In this paper we have explored indoor tracking technologies by looking into the main technologies of indoor positioning. 
We have looked at graph based techniques which utilizes low proximity technologies such as: NFC, RFID, and Bluetooth. 
In this context we regard Bluetooth as a low proximity technology. 
Beside the low proximity techniques we have looked into fingerprinting technologies which is Wi-Fi based and we explored some hybrid techniques where low proximity technologies are intertwined with Wi-Fi. \\

Both techniques looks promising, but they have their advantages and drawbacks. 
The graph-based techniques have relative high accuracy as the tags can be positioned such that they report the position where it is needed, but it requires a complex and new infrastructure implemented into the area where it is to be used. \\

Purely Wi-Fi based fingerprinting techniques can in most cases use existing infrastructure, as many buildings today  have Wi-Fi installed, but the technique suffer from low accuracy.
Though system are being developed which increase the accuracy~\cite{Youssef2005}, but has other drawbacks e.g. it requires a specialized WLAN-driver in the user device. \\

Hybrid systems are able to utilize the best of each category, but they still have drawbacks. 
As they can utilize the Wi-Fi new infrastructure is only needed for the low proximity devices.
In this way the investment in new infrastructure is reduced compared to graph based techniques
Hybrid system improves the overall accuracy compared to Wi-Fi. \\

Most of the techniques we have discovered have relative little computational requirements. 
Fingerprinting often relies on searching through a fingerprinting map. 
The computation can be moved to either the device or a server, but the server is the most obvious choice as it already contains the fingerprinting map. 
Using hybrid techniques reduces the search space of fingerprinting and thereby the required computation. \\

The low proximity techniques have low computational power as it only requires a lookup in a hashmap, or similar, to get the position of the device that the user has passed. 
If it is combined with the Max Speed limitation (see section~\ref{sec:speed}, the computation is slightly larger as we must compute the position based on a velocity vector. 
The computation is likely to be placed on the server. 
If it relies on dumb tags, the device must report which tag it has seen to the server in order to get its position. 
Low proximity techniques also requires a map of the building.\\

Based on the available technologies of today and not least the currently available infrastructure, we do not believe that one method of indoor tracking is superior to the others.
We believe that model-based is the best technique to get the most precise data, but the infrastructure that is required to use this technique needs to be implemented and is a huge task, as it requires a lot of sensors to be installed. 
Fingerprinting is easier to implement as the infrastructure using Wi-Fi signals exists, but research shows this is not precise and requires more computational power to use. 
We therefore believe that none of these are a general right choice, but the individual use case determines which applies the best.
% Hybrid technologies are most likely the best option but it is not as developed as the two pure technologies. 